Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Jessica, Pinaire"'
Publikováno v:
PLoS ONE, Vol 14, Iss 5, p e0215649 (2019)
BackgroundCurrently, cardiovascular disease (CVD) is widely acknowledged to be the first leading cause of fatality in the world with 31% of all deaths worldwide and is predicted to remain as such in 2030. Furthermore, CVD is also a major cause of mor
Externí odkaz:
https://doaj.org/article/f9d8b76fe6fa4d7b9e0e1bd176fc73b4
Autor:
Pascal Poncelet, Jessica Pinaire, Jérôme Azé, Paul Landais, Christophe Genolini, Sandra Bringay
Publikováno v:
Health informatics journal. 27(3)
Acute coronary syndrome (ACS) in women is a growing public health issue and a death leading cause. We explored whether the hospital healthcare trajectory was characterizable using a longitudinal clustering approach in women with ACS. From the 2009–
Publikováno v:
MIE
Study of trajectory of care is attractive for predicting medical outcome. Models based on machine learning (ML) techniques have proven their efficiency for sequence prediction modeling compared to other models. Introducing pattern mining techniques c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::614e9ce4a90bdff48623ec82bcde6210
https://doi.org/10.3233/shti210167
https://doi.org/10.3233/shti210167
Autor:
Jessica, Pinaire, Etienne, Chabert, Jérôme, Azé, Sandra, Bringay, Pascal, Poncelet, Paul, Landais
Publikováno v:
Studies in health technology and informatics. 281
Study of trajectory of care is attractive for predicting medical outcome. Models based on machine learning (ML) techniques have proven their efficiency for sequence prediction modeling compared to other models. Introducing pattern mining techniques c
Autor:
Pascal Poncelet, Sandra Bringay, Christophe Genolini, Jérôme Azé, Jessica Pinaire, Paul Landais
Publikováno v:
Techniques et sciences informatiques. 37:65-81
Autor:
Jessica, Pinaire, Jérôme, Azé, Sandra, Bringay, Pascal, Poncelet, Christophe, Genolini, Paul, Landais
Publikováno v:
Studies in health technology and informatics. 247
A better knowledge of patient flows would improve decision making in health planning. In this article, we propose a method to characterise patients flows and also to highlight profiles of care pathways considering times and costs. From medico-adminis
Autor:
Jessica Pinaire, Jérôme Azé, Sandra Bringay, Pascal Poncelet, Christophe Genolini, Paul Landais
Publikováno v:
4e édition du Symposium sur l'Ingénierie de l'Information Médicale
SIIM: Symposium Ingénierie de l’Information Médicale
SIIM: Symposium Ingénierie de l’Information Médicale, Nov 2017, Toulouse, France
HAL
SIIM: Symposium Ingénierie de l’Information Médicale
SIIM: Symposium Ingénierie de l’Information Médicale, Nov 2017, Toulouse, France
HAL
National audience; A better knowledge of patient flows can be decisive for health planning. In this article, we propose a method to characterise patients flow but also to highlight profiles of care pathways times and costs. From the medical-administr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1630fc0015e0b4bd04551bde400d2d07
https://hal.archives-ouvertes.fr/hal-01652800/file/siim-2017-flux.pdf
https://hal.archives-ouvertes.fr/hal-01652800/file/siim-2017-flux.pdf
Publikováno v:
Health Information Science and Systems
Health Information Science and Systems, BioMed Central, 2017, 5 (1), ⟨10.1007/s13755-017-0020-2⟩
Health Information Science and Systems, BioMed Central, 2017, 5 (1), ⟨10.1007/s13755-017-0020-2⟩
BackgroundPatient healthcare trajectory is a recent emergent topic in the literature, encompassing broad concepts. However, the rationale for studying patients’ trajectories, and how this trajectory concept is defined remains a public health challe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7051f434efe0a39c968b24c09cf9109a
https://hal.archives-ouvertes.fr/hal-01566986/document
https://hal.archives-ouvertes.fr/hal-01566986/document
Publikováno v:
16ème Conférence Internationale Francophone sur l’Extraction et Gestion des Connaissances
EGC: Extraction et Gestion des Connaissances
EGC: Extraction et Gestion des Connaissances, Jan 2016, Reims, France. pp.457-462
HAL
EGC: Extraction et Gestion des Connaissances
EGC: Extraction et Gestion des Connaissances, Jan 2016, Reims, France. pp.457-462
HAL
International audience; Dans cette démonstration, nous proposons une application de visuali-sation des résultats de la fouille de données séquentielles. Pour illustrer le fonc-tionnement de cette application, nous avons utilisé des données PMSI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8a936478e77db1ab2a541daff4a621bd
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01288468/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01288468/document
Publikováno v:
2e atelier de Gestion et Analyse des données Spatiales et Temporelles
GAST: Gestion et Analyse des données Spatiales et Temporelles
GAST: Gestion et Analyse des données Spatiales et Temporelles, IRISA, Jan 2016, Reims, France
HAL
GAST: Gestion et Analyse des données Spatiales et Temporelles
GAST: Gestion et Analyse des données Spatiales et Temporelles, IRISA, Jan 2016, Reims, France
HAL
National audience; L'extraction de motifs séquentiels permet d'identifier les séquences fréquentes d'événements ordonnés. Afin de résoudre le problème du grand nombre de motifs obtenus, nous proposons l'extension pour les motifs séquentiels
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6f97869f29cfdb64885fae944a16178a
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01288459
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01288459